Master Thesis

Application process

Master theses can be applied for all year round. Please send your application to the supervisor of the respective topic. Please use our application form and attach your curriculum vitae, a current transcript of grades as well as any existing diplomas to your application. In the case of unsolicited applications, we additionally ask you to describe your intention briefly but convincingly in the text of your e-mail.

Prerequisites

Course of study Conditions
Arbeitsmarkt und Personal 5 ECTS of the chair available in the module catalogue or application for exemption
Economics application for exemption
Finance, Auditing, Controlling, Taxation application for exemption
Gesundheitsmanagement und Gesundheitsökonomie application for exemption
International Business Studies none (work must be written in English)
International Information Systems none
Management application for exemption
Marketing application for exemption
Maschinenbau (Studienrichtung International Production Engineering and Management) attended module at the chair
Sozialökonomik attended module at the chair or application for exemption
Wirtschaftsingenieurwesen attended module (of group M7) at the chair
Wirtschaftspädagogik application for exemption

Open Topics

Topic Supervisor

While research has spent a lot of effort to study how digital health technology needs to be designed and developed to promote a positive health behavior change, ethical considerations that arise with the use of such technologies are often ignored. Critics argue that behavior change techniques (e.g., digital nudging, persuasive technology) are manipulative and undermine people’s freedom of choice. Moreover, the use of digital health technologies is usually associated with a massive collection of sensitive data that has the chance to further threaten the autonomy of individuals. This thesis aims to address ethical questions that arise with the use of behavior change techniques in digital health technologies. Questions that could be answered are: How do individuals perceive morals in relation to digital health technology? What are the design principles and guidelines that need to be considered when implementing digital health behavior change techniques? Which forms of behavior change interventions are considered to be a threat to the individual autonomy, which are not? Different methodologies (qualitative and quantitative) can be used to answer these and further questions. Moreover, a systematic literature review can be conducted to summarize the major findings from past research in this area. The thesis and the application can be handed in in German or English. Please apply to david.horneber@fau.de by using the chair’s application form together with all of your attachments.
David Horneber

Many large commercial online platforms use recommender systems to display individualized contents to their users, including shopping items, news reports, or job offers. While heavily contributing to the economic success of the companies operating these platforms, several studies have shown that the application of such recommender systems can direct the users into a “filter bubble” by continuously narrowing the diversity of the contents displayed to the user. The goal of this thesis is to explain and analyze this effect and its consequences within an application area of choice (e.g., social media platforms) by conducting either a structured literature review or an empirical study. The thesis can be written in English or German. Please apply to kian.schmalenbach@fau.de by using the chair’s application form together with all of your attachments.
Kian Schmalenbach

In this thesis students should analyze digital work systems. These work systems can either be changed because of a new digital technology being implemented or suffer from some challenges such that a recommendation on how to improve the design of the work system is required. In this thesis students should conducted interviews with participants of these work systems and use work system theory to analyze them. This thesis should be written with partners from industry. Students can also develop a teaching case that can be used to teach these lessons learnt to students and managers. This thesis and the related application can be handed in in German or English.Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments.
Prof. Dr. Sven Laumer

In this thesis student should focus on technostress, its causes and consequences. This can be done by case studies and interviews with people working in organizations. The master thesis can also consist of literature analysis of studies reported in the literature to summarize the major lessons learnt from past research in this area. Another opportunity is to develop guidelines what organizations and individuals need to consider in this area. Students can also develop a teaching case that can be used to teach these lessons learnt to students and managers. This thesis and the related application can be handed in in German or English. Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments.
Prof. Dr. Sven Laumer

People Analytics is a data-driven approach for managing an organization’s employee resources. In this context, increasing digitalization and the associated growth in available data enables managers to support their human resources management (HRM) activities through IT-based techniques based on Big Data. In the course of this thesis students will focus on People Analytics with a special focus on Big Data and artificial intelligence from a theoretical and above all practical perspective. They might apply data analytic techniques to specific people analytic questions or they will analyze the general acceptance and context related factors of this approach. This thesis and the related application can be handed in in German or English.Please apply to sven.laumer@fau.de by using the chair’s application form together with all of your attachments.
Prof. Dr. Sven Laumer

Society is increasingly relying on data-driven models for automated decision-making processes. The algorithms behind these models and the data they work with are often biased due to the nature of historical data and noisiness in observations. Hence, practitioners and researchers are increasingly looking for ways to mitigate the bias in algorithms and data. In this thesis, various possible research questions can be focused on, e.g.: What are strategies to mitigate discrimination? How should algorithms be designed to mitigate discrimination? How can discrimination be discovered? Different methodologies can be chosen to answer these and further questions. These methodologies include qualitative research and literature reviews, as well as quantitative approaches. The thesis can be handed in in German or English. Please apply to florian.j.meier@fau.de by using the chair’s application form together with all of your attachments.
Florian Meier

Algorithmic decision-making and large-scale data collection processes promise to render organizations more productive, efficient, and rational. However, implementing such applications is changing the behavior of staff and people, inside and outside the organization. These behavioral changes affect the quality of work and decisions as well as the well-being of humans. Various possible research questions can be focused on in this thesis, including: What is the impact of such applications on managers’ effectiveness and quality of decision-making? Does the role of managers change as a result of using such applications? What is the impact of these applications on employee productivity, job satisfaction, motivation, and autonomy? What is the impact of these applications on organizational culture, structure, business processes, and strategy? The thesis can be handed in in German or English. Please apply to florian.j.meier@fau.de by using the chair’s application form together with all of your attachments.
Florian Meier

People Analytics is the data-driven approach to human resources management (HRM) from an internal and external perspective. Data-driven HRM can be defined as the interplay of management, knowledge, research, math, and computer science, consisting of the following seven pillars: Workforce Planning, Sourcing Analytics, Hiring Analytics, Onboarding Analytics, Performance Analytics, Turnover Analytics, and Well-Being Analytics. The goal of this research is to analyze one of the seven people analytics pillars to construct a teaching case for students or managers. This can either be done by conducting case studies, interviews, or empirical research with organizations using or willing to use data-driven approaches in their HRM, or by analyzing the literature for the major lessons learned from past research in the people analytics area. This thesis and the related application can be handed in in German or English. Please apply to florian.j.meier@fau.de by using the chair’s application form together with all of your attachments.
Florian Meier

Organizations try to implement digital technologies in a recruiting context to improve their recruiting processes and increase efficiency. The thesis aims to identify academic research within the field of AI recruitment by conducting a systematic literature review. This thesis and the related application can be handed in in German or English Please apply to jessica.ochmann@fau.de by using the chair’s application form together with all of your attachments.
Jessica Ochmann

Internet and technology based recruiting is already a common approach in human resource management (HRM) and e-recruiting has significantly spread in recent years. From an organizations point of view there are numerous advantages, e.g. increased speed of application handling. But what do candidates think of automated recruiting and the use of AI? The subject of this thesis is to analyze how job seekers assess automated recruiting and the use of AI in the recruiting process. For this purpose, interviews, focus groups or quantitative studies can be carried out. This thesis and the related application can be handed in in German or English. Please apply to jessica.ochmann@fau.de by using the chair’s application form together with all of your attachments.
Jessica Ochmann

With the advance of digital technologies, there are chances to decrease discrimination and increase inclusion within organizations. The thesis aims to examine if automated recruiting can lead to less descrimination within the recruiting process. For this purpose, interviews, focus groups or quantitative studies can be carried out. This thesis and the related application can be handed in in German or English. Please apply to jessica.ochmann@fau.de by using the chair’s application form together with all of your attachments.
Jessica Ochmann

In a professional world characterised by high fluctuation rates and constantly changing requirements regarding the competences needed, it is becoming increasingly important for individuals to be able to familiarise themselves with new topics quickly and easily. Digital technologies offer the possibility to strongly individualize the learning process. For example, the application of artificial intelligence (AI) methods can provide precisely tailored and detailed recommendations for personal development.The subject of this thesis is to analyze releant literature in this field. This thesis and the related application can be written in German or English. Please apply to jessica.ochmann@fau.de by using the chair’s application form together with all of your attachments.
Jessica Ochmann

Artificial intelligence (AI) can significantly contribute to inclusion, i.e. the participation of people with disabilities or serious illnesses in everyday life. The thesis aims to examine how individuals asses the use of AI in HR to enable inclusion.  For this purpose, interviews, focus groups or quantitative studies can be carried out. This thesis and the related application can be written in German or English. Please apply to jessica.ochmann@fau.de by using the chair’s application form together with all of your attachments.
Jessica Ochmann